Described herein are mobile sensing units for capturing raw data corresponding to certain characteristics of plants and their growing environment. Also described are computer devices and related methods for collecting user inputs, generating information relating to the plants and/or growing environment based on the raw data and user inputs, and displaying same.

An environmental impact assessment device includes: an input unit configured to accept an input of a utilization purpose of an ICT service from a user, the ICT service being a target of assessment of a reduction effect for an environmental load; a first identification unit configured to refer to a storage unit in which, for each existing case about the assessment, an assessment result about the reduction effect for the environmental load for each activity item and a utilization purpose of the ICT service in the existing case are stored in association with each other, and to identify an existing case associated with the input utilization purpose; a second identification unit configured to identify an activity item for which the reduction effect is highest, for each existing case identified by the first identification unit; an acquisition unit configured to acquire a value of a parameter for an assessment expression for the environmental load, the assessment expression being previously set for each of the activity item identified by the second identification unit and utilization of an apparatus relevant to the ICT service; and a calculation unit configured to substitute the value acquired by the acquisition unit into the assessment expression, and to calculate a value of the environmental load for each of the activity item identified by the second identification unit and the utilization of the apparatus, and thereby, simplifies the assessment of the environmental load reduction effect due to the ICT service.

Interaction events collected across disparate customer communication channels of an enterprise are processed to generate an encoded unique content item identifier for each content item referenced in an interaction event such that the content item is resolvable to a location in a content repository. A training data set is built using the interaction events thus processed and a multi-channel content recommendation model is trained using the training data set. The multi-channel content recommendation model thus trained stores data points representing intersections of customers and content items that the enterprise has been tracking, with each data point having an effectiveness score for an associated content item. The multi-channel content recommendation model thus trained can be queried by content designers of the disparate customer communication channels through a recommender application for content recommendations based on the effectiveness of the content, agnostic to the disparate customer communication channels.

Information defining a plurality of states, a plurality of transitions, an initial state, and a final state is received from a user. The user may also provide additional information including pre-conditions and post-conditions for one or more transitions. Context information including one or more context variables and context variable values is generated based on the information provided by the user. A first plurality of possible paths between the initial state and the final state is automatically identified, wherein each path traverses at least one state and at least one transition. A second plurality of paths is identified from among the plurality of paths, based on the context information and the pre-conditions defined by the user. A Q-value is determined for each path in the second plurality of paths, using the rewards. A path having a highest Q-value is selected and presented to the user as a BPM. An acceptance or rejection of the proposed BPM is received from the user. Reward values associated with transitions in the selected path are updated, if the user accepts the proposed BPM.

An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.

A system and method are disclosed for interactive product assortment planning and visualization by receiving product attribute values for items of a product assortment is disclosed. Embodiments include displaying icons on an interactive visualization, connecting the icons with transferable demand links, identifying items to be removed from a product assortment, and transporting items among one or more supply chain entities.

A system and method are disclosed for interactive product assortment planning and visualization by receiving product attribute values for items of a product assortment is disclosed. Embodiments include displaying icons on an interactive visualization, connecting the icons with transferable demand links, identifying items to be removed from a product assortment, and transporting items among one or more supply chain entities.

An engineering assistant system 1 includes: an engineering server 10 that issues a work list including information related to work necessary for performing the engineering of a process control system 100; and an at least one engineering client 20 that grants work authority for each worker based on the work list issued by the engineering server 10 and makes it possible to perform work on a constituent apparatus that constitutes the process control system 100 within a range of granted work authority.

A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.

A computer system and computer-implemented method for retail merchandise planning, including promotional product selection, price optimization and planning. According to an embodiment, the computer system for generating an electronic retail plan for a retailer comprises, a data staging module configured to input retail sensory data from one or more computer systems associated with the retailer; a data processing module configured to pre-process the inputted retail sensory data; a data warehouse module configured to store the inputted retail sensory data and the pre-processed retail sensory data; a state model module configured to generate a retailer state model for modeling operation of the retailer based on the retail sensory data; a calibration module configured to calibrate the state model module according to one or more control parameters; and an output module for generating an electronic retail plan for the retailer based on the retailer state model.